Investment Rating - The report does not explicitly provide an investment rating for the industry or specific companies involved. Core Insights - DeepSeek's significant cost advantages in training and inference have led to substantial market impacts, including a notable drop in Nvidia's stock price and market capitalization [2][11][12] - The introduction of DeepSeek's models has the potential to disrupt existing AI companies by lowering the barriers to entry for smaller firms and individuals, thereby increasing overall demand for computational resources [15][16] Summary by Sections Section on DeepSeek's Market Impact - DeepSeek achieved the top position in download rankings on both the Chinese and US App Store, coinciding with a major drop in the semiconductor index and Nvidia's stock [2] - Nvidia's market value decreased by nearly $600 billion, marking one of the largest single-day market cap losses in history [2] Section on Cost Structure - DeepSeek's training costs for their V3 model were reported to be under $6 million, utilizing approximately 2000 H800 GPUs [6][7] - The inference cost for DeepSeek's models is significantly lower than that of OpenAI, with DeepSeek charging only 3% of OpenAI's rates for similar token inputs and outputs [7][9] Section on Training Innovations - DeepSeek implemented innovative training strategies that reduced costs, particularly by optimizing the supervised fine-tuning (SFT) process [9][10] - The team utilized pure reinforcement learning (RL) without human feedback, achieving performance comparable to OpenAI's models [9][10] Section on Future Implications for AI Industry - DeepSeek's advancements may lead to increased competition among AI firms, particularly those relying on self-developed large models [12][13] - The report suggests that while Nvidia's stock may have been negatively impacted in the short term, the overall demand for their chips could increase as AI commercialization accelerates [14][16]

Core Viewpoint - Morgan Stanley believes that China's Generative AI (GAI) development is at the beginning of its second phase, with Alibaba positioned as a key player in the Infrastructure as a Service (IAAS) value chain, likely to outperform peers in this phase and potentially benefit from the third phase of applications [2][3]. Phase Summaries - **Phase 1**: Development of large language models (LLMs), focusing on building and optimizing LLMs [5]. - **Phase 2**: Application of GAI in existing applications and services, currently at the beginning stage where companies are exploring value creation models [6]. - **Phase 3**: Surge in internet service consumption as GAI applications become widespread, leading to significant financial gains for internet operators [7]. - **Phase 4**: Emergence of native GAI "killer applications" that will fundamentally change market competition and introduce new business models [8]. Infrastructure as a Service (IAAS) Insights - The report highlights that companies in the IAAS value chain will perform well in the second phase of GAI development, with revenue expectations likely to be positively revised. Alibaba is identified as the most promising stock in this area [11][12]. - Tencent, while holding a significant market share in China's IAAS, is viewed more as a beneficiary of AI applications rather than a primary player in the IAAS space [12][13]. Other Key Players - **Kuaishou**: Identified as an undervalued AI beneficiary, with expectations that AI will significantly enhance user engagement and monetization capabilities. The AI video/image generator Kling is projected to have over 6 million users by December 2024, indicating substantial monetization potential in various commercial verticals [15]. - **Baidu**: Positioned as both an IAAS cloud value chain player and a potential GAI application beneficiary. The company's stock outlook is contingent on the transformation of its core advertising and cloud business narratives [16].